{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "__Compare FWI result with true model for the Overthrust model__\n",
    "\n",
    "Daniel Köhn \n",
    "Kiel, 16/07/2016"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "__Import Libraries__"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import matplotlib as mpl\n",
    "import numpy as np\n",
    "from matplotlib.colors import LightSource, Normalize\n",
    "from matplotlib.pyplot import gca\n",
    "from pylab import rcParams\n",
    "from matplotlib import rc\n",
    "from matplotlib.ticker import FormatStrFormatter\n",
    "import matplotlib.ticker as mtick\n",
    "from mpl_toolkits.axes_grid1 import make_axes_locatable\n",
    "from scipy.ndimage.filters import gaussian_filter\n",
    "import pickle"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Import external colormap**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [],
   "source": [
    "fp = open('../cmap_cm.pkl', 'rb')\n",
    "my_cmap = pickle.load(fp)\n",
    "fp.close()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "__FD grid dimensions__"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [],
   "source": [
    "DH = 0.05\n",
    "NX = 1952\n",
    "NY = 1392\n",
    "stage = 11"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [],
   "source": [
    "x_p500_outcrop_pos = 69.779"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "__Define fonts__"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [],
   "source": [
    "FSize = 15\n",
    "font = {'color':  'black',\n",
    "        'weight': 'normal',\n",
    "        'size': FSize}\n",
    "mpl.rc('xtick', labelsize=FSize) \n",
    "mpl.rc('ytick', labelsize=FSize) \n",
    "rcParams['figure.figsize'] = 16, 9"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "__Read FWI result and true model__"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [],
   "source": [
    "#f = open(\"11_01_2019_s140_fmax_80Hz_gauss_var_sx_1p5_sz_0p5_full_offset/modelTest_vs_stage_\" + str(stage) + \".bin\")\n",
    "f = open(\"../../start/Kleinneudorf_init_s140.vs\")\n",
    "data_type = np.dtype ('float32').newbyteorder ('<')\n",
    "mod_true = np.fromfile (f, dtype=data_type)\n",
    "mod_true = mod_true.reshape(NX,NY)\n",
    "mod_true = np.transpose(mod_true)\n",
    "mod_true = np.flipud(mod_true)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [],
   "source": [
    "#f = open(\"11_01_2019_s140_fmax_80Hz_gauss_var_sx_1p5_sz_0p5_full_offset/modelTest_rho_stage_\" + str(stage) + \".bin\")\n",
    "f = open(\"../../start/Kleinneudorf_init_s140.rho\")\n",
    "data_type = np.dtype ('float32').newbyteorder ('<')\n",
    "fwi = np.fromfile (f, dtype=data_type)\n",
    "fwi = fwi.reshape(NX,NY)\n",
    "fwi = np.transpose(fwi)\n",
    "fwi = np.flipud(fwi)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "__Find minimum values > 0__"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "vsmax =  682.644\n",
      "rhomax =  2075.59\n"
     ]
    }
   ],
   "source": [
    "EST_MINMAX = 0\n",
    "if(EST_MINMAX==1):\n",
    "    \n",
    "    vsmin = 1e9\n",
    "    rhomin = 1e9\n",
    "\n",
    "    for i in range(0,NY-1):\n",
    "        for j in range(0,NX-1):\n",
    "        \n",
    "            if(fwi[i,j]<vsmin and fwi[i,j] > 0.0):\n",
    "                rhomin = fwi[i,j]\n",
    "            \n",
    "    for i in range(0,NY-1):\n",
    "        for j in range(0,NX-1):\n",
    "        \n",
    "            if(mod_true[i,j]<vsmin and mod_true[i,j] > 0.0):\n",
    "                vsmin = mod_true[i,j]\n",
    "            \n",
    "    print(\"vsmin = \", vsmin)\n",
    "    print(\"rhomin = \", rhomin)\n",
    "\n",
    "print(\"vsmax = \", np.max(mod_true))\n",
    "print(\"rhomax = \", np.max(fwi))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "__Wavefield clip value__ "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [],
   "source": [
    "# parameters from p500 FWI result\n",
    "#vsmin = 58.0\n",
    "#vsmax = 910.0\n",
    "#rhomin = 1450.0\n",
    "#rhomax = 2640.0\n",
    "\n",
    "# Parameters from pnorte\n",
    "#vsmin = 100.0\n",
    "#vsmax = 710.0\n",
    "#rhomin = 1550.0\n",
    "#rhomax = 2380.0\n",
    "\n",
    "# Parameters from p500 FWI result\n",
    "vsmin = 43.0\n",
    "vsmax = 749.0\n",
    "rhomin = 1550.0\n",
    "rhomax = 2455.0"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "__Define Axis__"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [],
   "source": [
    "x = np.arange(0.0, DH*NX, DH)\n",
    "y = np.arange(0.0, DH*NY, DH)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "__Define SubPlot__"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [],
   "source": [
    "def do_plot(n, model, cm, an, an1, title, vpmin, vpmax):\n",
    "    \n",
    "    ax=plt.subplot(1, 2, n)\n",
    "    \n",
    "    rc('font',**{'family':'sans-serif','sans-serif':['Helvetica']})\n",
    "    rc('text', usetex=True)\n",
    "    \n",
    "    im1 = plt.imshow(model, cmap=cm, interpolation='none', extent=[0.0,NX*DH,0.0,NY*DH], vmin=vpmin, vmax=vpmax, aspect=1)\n",
    "    # mark outcrop by arrow\n",
    "    #arr = plt.arrow(x_p500_outcrop_pos, 0, 0, 2, edgecolor='black', head_width=3, head_length=4)\n",
    "    \n",
    "    a = gca()\n",
    "    a.set_xticklabels(a.get_xticks(), font)\n",
    "    a.set_yticklabels(a.get_yticks(), font)\n",
    "    a.yaxis.set_major_formatter(mtick.FormatStrFormatter('%.0d'))\n",
    "    a.xaxis.set_major_formatter(mtick.FormatStrFormatter('%.0d'))\n",
    "    #a.add_patch(arr)\n",
    "    #plt.axis('scaled')\n",
    "    plt.title(title, fontdict=font)\n",
    "    if n==1:\n",
    "        plt.ylabel('Depth [m]', fontdict=font)    \n",
    "    plt.xlabel('Distance [m]', fontdict=font)\n",
    "    plt.ylim(0, 50)\n",
    "    plt.gca().invert_yaxis()\n",
    "    if n==2:\n",
    "        ax.yaxis.set_major_formatter(plt.NullFormatter())\n",
    "    \n",
    "    # add annotation\n",
    "    # plt.text(4,50,an1,fontdict=font,color='white',size=20)\n",
    "    \n",
    "    # fit and label colorbar\n",
    "    divider = make_axes_locatable(ax)\n",
    "    cax = divider.append_axes(\"right\", size=\"2.5%\", pad=0.05)\n",
    "    cbar = plt.colorbar(im1, cax=cax)\n",
    "    cbar.set_label(an, fontdict=font, labelpad=3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "__Plot SubPlots__"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\daniel_koehn\\Anaconda3\\lib\\site-packages\\matplotlib\\font_manager.py:1328: UserWarning: findfont: Font family ['sans-serif'] not found. Falling back to DejaVu Sans\n",
      "  (prop.get_family(), self.defaultFamily[fontext]))\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1152x648 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.close('all')\n",
    "plt.figure()\n",
    "\n",
    "#do_plot(1, mod_true, 'gist_gray_r', 'Vs [m/s]', '(a)', r\"Kleinneudorf FWI (profile 500)\", vsmin, vsmax)\n",
    "#do_plot(2, fwi, 'afmhot_r', r'Density [kg/$\\bf{\\sf{m^3}}$]', '(b)', \"\", rhomin, rhomax)\n",
    "\n",
    "do_plot(1, mod_true, 'magma_r', r'Vs [m/s]', '(a)', \"Kleinneudorf FWI (profile s140)\", vsmin, vsmax)\n",
    "do_plot(2, fwi, 'afmhot_r', r'Density [kg/$\\bf{\\sf{m^3}}$]', '(b)', \"\", rhomin, rhomax)\n",
    "\n",
    "plt.savefig('stage_' + str(stage) + '.pdf', bbox_inches='tight', format='pdf')\n",
    "#plt.savefig('stage_' + str(stage) + '.png', bbox_inches='tight', format='png',dpi=100)\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "kernelspec": {
   "display_name": "Python [default]",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}
